The era of Human-Centric AI
"How many roles can we automate?" is a race to the bottom. The real question is how to build an ecosystem where AI makes your top talent untouchable.
LinkedIn
Where we post
We use LinkedIn to share what we are thinking about, what we are building, and occasionally what we disagree with. If you follow us there you will get the unfiltered version.
Our page
The company page is under xsingular-ai. That is the one we actually run — anything else is not us.
https://www.linkedin.com/company/xsingular-aiWhat we tend to post
Mostly technical takes on AI in production. Sometimes a position on something we feel strongly about. We do not post for engagement — we post when we have something worth saying.
Some recent posts
A few things we have shared recently. Most of them connect to something longer on xTheus if you want to go deeper.
The foundation of 2026 AI breakthroughs
Effective AI strategy starts with understanding its roots. A comprehensive timeline of the history of Artificial Intelligence — from theoretical milestones to practical deployment.
World Models: the next massive leap in AI?
Yann LeCun's AMI Labs secured $1.03B to build AI architectures that understand physics, time, and causality. Why this paradigm shift matters for complex reasoning and autonomous systems.
Pinecone vs Milvus in production
A comprehensive technical comparison of two leading vector databases: architectures, scalability constraints, and deployment trade-offs for enterprise-grade GenAI systems.
Understanding AI history to build better AI strategy
The current AI landscape is the result of decades of theoretical development and structural milestones. Understanding this trajectory is essential for organizations deploying AI today.
Human-Centric AI: from automation to augmentation
The differentiator between companies experimenting with AI and those transforming their operations isn't the size of the model — it's the mindset. Three transitions leadership must master.
The liquid foundation model era
Traditional models are born frozen. For high-stakes sectors like Mining, Banking, or Logistics, relying on cloud-hosted models for physical operations is a severe operational error.
"AI will replace humans" is a flawed narrative
The 2026 reality: elite professionals don't execute tasks, they orchestrate a Silicon-Based Workforce. Elite organizations are building Agent-Native Architectures from scratch.
The era of AI pilots is officially over
In critical sectors like Mining, Banking, and Logistics, experimentation is no longer enough. Operations demand verifiable results: XAI, executable guardrails, and Decision Intelligence.
Topics we come back to
- Getting AI to work in production, not just in demos.
- Agent systems and what it actually takes to run them responsibly.
- The gap between what foundation models promise and what they deliver.
- Decision-making under uncertainty, traceability, and why guardrails matter.